• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.193-204
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• 2022

The 2018 Seoul Zero Pay is a policy actively promoted by the government as an economic stimulus package for small business owners and the self-employed who are experiencing economic depression due to COVID-19. However, the controversy over the effectiveness of Zero Pay continues even after two years have passed since the implementation of the policy. Zero Pay is a joint QR code mobile payment service introduced by the government, Seoul city, financial companies, and private simple payment providers to reduce the burden of card merchant fees for small business owners and self-employed people who are experiencing economic difficulties due to the economic downturn., it was attempted in the direction of economic revitalization for the return of alleyways[1]. Therefore, this study intends to draw implications for improvement measures so that the ongoing zero-pay can be further activated and the economy can be settled normally. The analysis results of this study are as follows. First, it shows the effect of increasing the income of small business owners by inducing consumption in alleyways through the economic revitalization policy of Zero Pay. Second, the issuance and distribution of Zero Pay helps to revitalize the local economy and contribute to the establishment of a virtuous cycle system. Third, stable operation is being realized by the introduction of blockchain technology to the Zero Pay platform. In terms of academic significance, the direction of Zero Pay's policies and systems was able to identify changes in the use of Zero Pay through big data analysis. The implementation of the zero-pay policy is in its infancy, and there are limitations in factors for examining the consumer image perception of zero-pay as there are insufficient prior studies. Therefore, continuous follow-up research on Zero Pay should be conducted.

• Korean Journal of Environmental Agriculture
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• v.41 no.2
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• pp.101-107
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• 2022

BACKGROUND: Soil amendment was necessary applied for the sand that had been used to root zone of green ground in golf course because of its low water retention power and cation exchangeable capacity. This study was conducted to evaluate the effect of the mixed ratio of peat moss and coconut coir as soil amendment materials on the soil physicochemical properties applied to rootzone based on sand. METHODS AND RESULTS: The soil amendments were blended at 0, 3, 5, 7 and 10% by soil volume. The pH in the peat moss treatment was lower than that of control (0% soil amendment), and pH and electrical conductivity (EC) in the coconut coir were higher. The blending ratio of peat moss was negatively correlated with pH of rootzone soil (p<0.01), and that of coconut coir positively with EC (p<0.01). As compared with control, capillary porosity, the physical factors such as air-filled porosity, total porosity, and hydraulic conductivity of rootzone soil were increased by applying peat moss and coconut coir. For correlation coefficients between percentage of soil amendments and soil physical factors, peat moss and coconut coir were positively correlated with porosity and hydraulic conductivity (p<0.01). CONCLUSION(S): These results indicated that the application of peat moss and coconut coir affected on the change of physicochemical properties of rootzone soil, and improved soil porosity and hydraulic conductivity.

• Smart Structures and Systems
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• v.29 no.1
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• pp.129-140
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• 2022

The effectiveness of system identification, damage detection, condition assessment and other structural analyses relies heavily on the accuracy and reliability of the measured data in structural health monitoring (SHM) systems. However, data anomalies often occur in SHM systems, leading to inaccurate and untrustworthy analysis results. Therefore, anomalies in the raw data should be detected and cleansed before further analysis. Previous studies on data anomaly detection mainly focused on just single type of data anomaly for denoising or removing outliers, meanwhile, the existing methods of detecting multiple data anomalies are usually time consuming. For these reasons, recognising multiple anomaly patterns for real-time alarm and analysis in field monitoring remains a challenge. Aiming to achieve an efficient and accurate detection for multi-type data anomalies for field SHM, this study proposes a pattern-recognition-based data anomaly detection method that mainly consists of three steps: the feature extraction from the long time-series data samples, the training of a pattern recognition neural network (PRNN) using the features and finally the detection of data anomalies. The feature extraction step remarkably reduces the time cost of the network training, making the detection process very fast. The performance of the proposed method is verified on the basis of the SHM data of two practical long-span bridges. Results indicate that the proposed method recognises multiple data anomalies with very high accuracy and low calculation cost, demonstrating its applicability in field monitoring.

• Geomechanics and Engineering
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• v.28 no.6
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• pp.599-611
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• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.371-379
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• 2022

The environment in Kosovo is a topic of concern for the citizens and the state because of the temperatures that affect the health of the citizens and the climate around the world. Kosovo's climate is related to its geographical position. Stretching in the middle latitude, Kosovo's climate depends on the amount of heat coming from the Sun, the proximity of the Adriatic Sea, the Vardar valley, the openness to the north. In order to better understand the climatic features of Kosovo, one must know the elements of the climate such as: sunshine, temperature, precipitation, atmospheric pressure, winds. The Meteorological Institute of Kosovo is responsible for measuring temperatures in Kosovo since 2014 and until now 12 meteorological stations have been operationalized with automatic measurement and real-time data transfer to the central system for data collection and archiving. The hydrometeorological institute lacks an application for measuring temperatures in all the countries of Kosovo. Software applications are generally built to suit the requirements of different governments and clients in order to enable easier management of the jobs they operate on. One of the forms of application development is the development of mobile applications based on android. The purpose of the work is to create a mobile application based on the Android operating system that aims to display information about the weather, this type of application is necessary and important for users who want to see the temperature in different places in Kosovo, but also the world. This type of application offers many options such as maximum temperature, minimum temperature, humidity, and air pressure. The built application will have real and accurate data; this will be done by comparing the results with other similar applications. Such an application is necessary for everyone, especially for those people whose daily work is dependent on the weather or even for those who decide to spend their vacations, such as summer or winter. In this paper, comparisons are also made within android applications for tablets, televisions and smart watches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1486-1494
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• 2021

Character recognition is a technology required in various platforms, such as smart parking and text to speech, and many studies are being conducted to improve its performance through new attempts. However, with low-quality image used for character recognition, a difference in resolution of the training image and test image for character recognition occurs, resulting in poor accuracy. To solve this problem, this paper designed an end-to-end learning neural network that combines image super-resolution and character recognition so that the character recognition model performance is robust against various quality data, and implemented an alternative whole learning algorithm to learn the whole neural network. An alternative end-to-end learning and recognition performance test was conducted using the license plate image among various text images, and the effectiveness of the proposed algorithm was verified with the performance test.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.4
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• pp.343-352
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• 2022

Co/Al₂O₃ nanopowder was used as a catalyst to investigate the effect of catalyst support, reduction temperature, sodium borohydride (NaBH₄) concentration, sodium hydroxide (NaOH) concentration, and reaction temperature on the characteristics of NaBH₄ hydrolysis. The Co/Al₂O₃ nanopowder showed a high catalytic activity among various catalysts. Catalyst reduction at 250℃ exhibited a relatively good activity. The activity decreased with an increase in the NaBH₄ concentration. Conversely, the activity increased and then decreased with an increase in the NaOH concentration. Additionally, the activity increased with an increase in the reaction temperature. The value of apparent activation energy was 40.81 kJ/mol, which was lower than the other Co-based catalysts. Thus, Co/Al₂O₃ nanopowder catalyst can be widely used for NaBH₄ hydrolysis owing to its superior catalytic activity.

• Fashion & Textile Research Journal
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• v.24 no.4
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• pp.471-478
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• 2022

In roadside workplaces, more attention should be paid to the safety of workers. The roadside workers underestimate the effect of the brightness of their clothes and judge that drivers will recognize them easily, and the drivers misjudge that the roadside workers are far away and that the vehicle can be stopped in sufficient time. Therefore, customized safety education reflecting this and wearing work clothes with certified visibility functions are required. In Korea, it is not compulsory for roadside workers and vehicle guide attendants to wear work clothes with a visibility function. In this study, the distance ahead perceived by drivers was measured using manikins wearing certified and non-certified reflective safety vests. The perception distance of the non-certified reflective safety vest was 1.4 times longer than that of the certified reflective safety vest, thus confirming the importance of wearing a certified reflective safety vest. To prevent roadside workers from suffering traffic accidents, we propose the enactment of a law that makes it mandatory for them to wear high-visibility safety clothing. Specifically, Article 32 of the Enforcement Regulation of the Road Traffic Act should include high-visibility safety clothing in life protection equipment, and additionally, to prevent secondary accidents, we propose the enactment of a law requiring the installation and wearing of certified reflective safety vests in vehicles.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.6
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• pp.594-602
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• 2022

Cast-resin transformers are widely installed in various electrical power systems because of their low operating cost and low influence on external environmental factors. However, when they have an internal defect during the manufacturing process or operation, a partial discharge (PD) occurs, and eventually destroys the insulation. In this paper, a Rogowski-type PD sensor was studied to replace commercial PD sensors used for the insulation diagnosis of power apparatus. The proposed PD sensor was manufactured with four different types of PCB-based winding structures, and it was analyzed in terms of the detection characteristics for standard calibration pulses and the changes of the output voltage according to the distance. The output increased linearly in accordance with the applied discharge amount. It was confirmed that the hexagon structure sensor had the highest sensitivity, because the winding cross-sectional area of the sensor was larger than others. In addition, as the distance from the defect increased, the output voltage of the sensors decreased by 7.32% on average. It was also confirmed that the attenuation rate according to the distance decreased as the input discharge amount increased. For the application of this new type sensor, PD electrode system was designed to simulate the void defect. Waveforms and PRPD patterns measured by the proposed PD sensors at DIV and 120% of DIV were the same as the results measured by MPD 600 based on IEC 60270. The proposed PD sensors can be installed on the inner wall of the transformer tank by coating its surfaces with a non-conductive material; therefore, it is possible to detect internal defects more effectively at a closer distance from the defect than the conventional sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.542-558
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• 2023

A digital focus index (DFI) is a value used to determine image focus in scientific apparatus and smart devices. Automatic focus (AF) is an iterative and time-consuming procedure; however, its processing time can be reduced using a general processing unit (GPU) and a multi-core processor (MCP). In this study, parallel architectures of a minimax search algorithm (MSA) are applied to two DFIs: range algorithm (RA) and image contrast (CT). The DFIs are based on a histogram; however, the parallel computation of the histogram is conventionally inefficient because of the bank conflict in shared memory. The parallel architectures of RA and CT are constructed using parallel reduction for MSA, which is performed through parallel relative rating of the image pixel pairs and halved the rating in every step. The array size is then decreased to one, and the minimax is determined at the final reduction. Kernels for the architectures are constructed using open source software to make it relatively platform independent. The kernels are tested in a hexa-core PC and an embedded device using Lenna images of various sizes based on the resolutions of industrial cameras. The performance of the kernels for the DFIs was investigated in terms of processing speed and computational acceleration; the maximum acceleration was 32.6× in the best case and the MCP exhibited a higher performance.